All Outputs (36)

Fuzzy data analysis methodology for the assessment of value of information in the oil and gas industry. (2018)
Conference Proceeding
VILELA, M., OLUYEMI, G. and PETROVSKI, A. 2018. Fuzzy data analysis methodology for the assessment of value of information in the oil and gas industry. In Proceedings of the 2018 IEEE international conference on fuzzy systems (FUZZ-IEEE 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article ID 8491628. Available from: https://doi.org/10.1109/FUZZ-IEEE.2018.8491628

To manage uncertainty in reservoir development projects, the Value of Information is one of the main factors on which the decision is based to determine whether it is necessary to acquire additional data. However, subsurface data is not always precis... Read More about Fuzzy data analysis methodology for the assessment of value of information in the oil and gas industry..

Evolutionary computation for optimal component deployment with multitenancy isolation in cloud-hosted applications. (2018)
Conference Proceeding
OCHEI, L.C., PETROVSKI, A. and BASS, J.M. 2018. Evolutionary computation for optimal component deployment with multitenancy isolation in cloud-hosted applications. In Proceedings of the 2018 IEEE international symposium on innovations in intelligent systems and applications (INISTA 2018), 3-5 July 2018, Thessaloniki, Greece. New York: IEEE [online], article ID 8466315. Available from: https://doi.org/10.1109/INISTA.2018.8466315

A multitenant cloud-application that is designed to use several components needs to implement the required degree of isolation between the components when the workload changes. The highest degree of isolation results in high resource consumption and... Read More about Evolutionary computation for optimal component deployment with multitenancy isolation in cloud-hosted applications..

Towards situational awareness of botnet activity in the Internet of Things (2018)
Conference Proceeding
MCDERMOTT, C.D., PETROVSKI, A.V. and MAJDANI, F. 2018. Towards situational awareness of botnet activity in the Internet of Things. In Proceedings of the 2018 International conference on cyber situational awareness, data analytics and assessment (Cyber SA 2018): cyber situation awareness as a tool for analysis and insight, 11-12 June 2018, Glasgow, UK. Piscataway: IEEE [online], article number 8551408. Available from: https://doi.org/10.1109/CyberSA.2018.8551408

An IoT botnet detection model is designed to detect anomalous attack traffic utilised by the mirai botnet malware. The model uses a novel application of Deep Bidirectional Long Short Term Memory based Recurrent Neural Network (BLSTMRNN), in conjuncti... Read More about Towards situational awareness of botnet activity in the Internet of Things.

Intelligent measurement in unmanned aerial cyber physical systems for traffic surveillance. (2016)
Conference Proceeding
PETROVSKI, A., RATTADILOK, P. and PETROVSKII, S. 2016. Intelligent measurement in unmanned aerial cyber physical systems for traffic surveillance. In Jayne, C. and Iliadis, L. (eds.) Engineering applications of neural networks: proceedings of the 17th International engineering applications of neural networks conference (EANN 2016), 2-5 September 2016, Aberdeen, UK. Communications in computer and information science, 629. Cham: Springer [online], pages 161-175. Available from: https://doi.org/10.1007/978-3-319-44188-7_12 161-175. Available from: https://doi.org/10.1007/978-3-319-44188-7_12

An adaptive framework for building intelligent measurement systems has been proposed in the paper and tested on simulated traffic surveillance data. The use of the framework enables making intelligent decisions related to the presence of anomalies in... Read More about Intelligent measurement in unmanned aerial cyber physical systems for traffic surveillance..

Designing a context-aware cyber physical system for smart conditional monitoring of platform equipment. (2016)
Conference Proceeding
MAJDANI, F., PETROVSKI, A. and DOOLAN, D. 2016. Designing a context-aware cyber physical system for smart conditional monitoring of platform equipment. In Jayne, C. and Iliadis, L. (eds.) Engineering applications of neural networks: proceedings of the 17th International engineering applications of neural networks conference (EANN 2016), 2-5 September 2016, Aberdeen, UK. Communications in computer and information science, 629. Cham: Springer [online], pages 198-210. Available from: https://doi.org/10.1007/978-3-319-44188-7_15

An adaptive multi-tiered framework, which can be utilised for designing a context-aware cyber physical system is proposed and applied within the context of assuring offshore asset integrity. Adaptability is achieved through the combined use of machin... Read More about Designing a context-aware cyber physical system for smart conditional monitoring of platform equipment..

Implementing the required degree of multitenancy isolation: a case study of cloud-hosted bug tracking system. (2016)
Conference Proceeding
OCHEI, L.C., PETROVSKI, A. and BASS, J.M. 2016. Implementing the required degree of multitenancy isolation: a case study of cloud-hosted bug tracking system. In Zhang, J., Miller, J.A. and Xu, X. (eds.) Proceedings of the 13th Institute of Electrical and Electronics Engineers (IEEE) International services computing conference 2016 (SCC 2016), 27 June - 2 July 2016, San Francisco, USA. Piscataway: IEEE [online], pages 379-386. Available from: https://doi.org/10.1109/SCC.2016.56

Implementing the required degree of isolation between tenants is one of the significant challenges for deploying a multitenant application on the cloud. This paper applies COMITRE (Component-based approach to multitenancy isolation through request re... Read More about Implementing the required degree of multitenancy isolation: a case study of cloud-hosted bug tracking system..

Evaluating degrees of tenant isolation in multitenancy patterns: a case study of cloud-hosted version control system (VCS). (2015)
Conference Proceeding
OCHEI, L.C., PETROVSKI, A. and BASS, J.M. 2015. Evaluating degrees of tenant isolation in multitenancy patterns: a case study of cloud-hosted version control system (VCS). In Proceedings of the 2015 International Information Society conference 2015 (i-Society 2015), 9-11 November 2015, London, UK. Piscataway: IEEE [online], pages 59-66. Available from: https://doi.org/10.1109/i-Society.2015.7366859

One of the key concerns of implementing multitenancy (i.e., serving multiple tenants with a single instance of an application) on the cloud is how to enable the required degree of isolation between tenants, so that the required performance of one ten... Read More about Evaluating degrees of tenant isolation in multitenancy patterns: a case study of cloud-hosted version control system (VCS)..

ClusterNN: a hybrid classification approach to mobile activity recognition. (2015)
Conference Proceeding
BASHIR, S., DOOLAN, D. and PETROVSKI, A. 2015. ClusterNN: a hybrid classification approach to mobile activity recognition. In Chen, L.L., Steinbauer, M., Khalil, I. and Anderst-Kotsis, G. (eds.) Proceedings of the 13th International advances in mobile computing and multimedia conference (MoMM 2015), 11-13 December 2015, Brussels, Belguim. New York: ACM [online], pages 263-267. Available from: https://doi.org/10.1145/2837126.2837140

Mobile activity recognition from sensor data is based on supervised learning algorithms. Many algorithms have been proposed for this task. One of such algorithms is the K-nearest neighbour (KNN) algorithm. However, since KNN is an instance based algo... Read More about ClusterNN: a hybrid classification approach to mobile activity recognition..

Evaluating degrees of multitenancy isolation: a case study of cloud-hosted GSD tools. (2015)
Conference Proceeding
OCHEI, L.C., BASS, J.M. and PETROVSKI, A. 2015. Evaluating degrees of multitenancy isolation: a case study of cloud-hosted GSD tools. In Proceedings of the 2015 International conference on cloud and autonomic computing (ICCAC 2015), 21-25 September 2015, Boston, USA. Piscataway: IEEE [online], pages 101-112. Available from: https://doi.org/10.1109/ICCAC.2015.17

Multitenancy is an essential cloud computing property where a single instance of an application serves multiple tenants. Multitenancy introduces significant challenges when deploying application components to the cloud due to the demand for different... Read More about Evaluating degrees of multitenancy isolation: a case study of cloud-hosted GSD tools..

Designing a context-aware cyber physical system for detecting security threats in motor vehicles. (2015)
Conference Proceeding
PETROVSKI, A., RATTADILOK, P. and PETROVSKI, S. 2015. Designing a context-aware cyber physical system for detecting security threats in motor vehicles. In Proceedings of the 8th International conference on security of information and networks (SIN'15), 8-10 September 2015, Sochi, Russia. New York: ACM [online], pages 267-270. Available from: https://doi.org/10.1145/2799979.2800029

An adaptive multi-tiered framework, which can be utilised for designing a context-aware cyber physical system is proposed in the paper and is applied within the context of providing data availability by monitoring electromagnetic interference. The ad... Read More about Designing a context-aware cyber physical system for detecting security threats in motor vehicles..

Automated inferential measurement system for traffic surveillance: enhancing situation awareness of UAVs by computational intelligence. (2014)
Conference Proceeding
RATTADILOK, P. and PETROVSKI, A. 2014. Automated inferential measurement system for traffic surveillance: enhancing situation awareness of UAVs by computational intelligence. In Proceedings of the 2014 IEEE symposium on computational intelligence in control and automation (CICA 2014), part of the 2014 IEEE symposium series on computational intelligence (SSCI 2014), 9-12 December 2014, Orlando, USA. New York: IEEE [online], article number 7013256, pages 229-236. Available from: https://doi.org/10.1109/CICA.2014.7013256

An adaptive inferential measurement framework for control and automation systems has been proposed in the paper and tested on simulated traffic surveillance data. The use of the framework enables making inferences related to the presence of anomalies... Read More about Automated inferential measurement system for traffic surveillance: enhancing situation awareness of UAVs by computational intelligence..

Self-learning data processing framework based on computational intelligence enhancing autonomous control by machine intelligence. (2014)
Conference Proceeding
RATTADILOK, P. and PETROVSKI, A. 2014. Self-learning data processing framework based on computational intelligence enhancing autonomous control by machine intelligence. In Proceedings of the 2014 IEEE symposium on evolving and autonomous learning systems (EALS 2014), part of the 2014 IEEE symposium series on computational intelligence (SSCI 2014), 9-12 December 2014, Orlando, USA. New York: IEEE [online], article number 7009508, pages 87-94. Available from: https://doi.org/10.1109/EALS.2014.7009508

A generic framework for evolving and autonomously controlled systems has been developed and evaluated in this paper. A three-phase approach aimed at identification, classification of anomalous data and at prediction of its consequences is applied to... Read More about Self-learning data processing framework based on computational intelligence enhancing autonomous control by machine intelligence..

Anomaly monitoring framework based on intelligent data analysis. (2013)
Conference Proceeding
RATTADILOK, P., PETROVSKI, A. and PETROVSKI, S. 2013. Anomaly monitoring framework based on intelligent data analysis. In Yin, H., Tang, K., Gao, Y., Klawonn, F., Lee, M., Weise, T., Li, B. and Yao, X. (eds.) Proceedings of the 14th International conference on intelligent data engineering and automated learning (IDEAL 2013), 20-23 October 2013, Hefei, China. Lecture notes in computer science, 8206. Berlin: Springer [online], pages 134-141. Available from: https://doi.org/10.1007/978-3-642-41278-3_17

Real-time data processing has become an increasingly important challenge as the need for faster analysis of big data widely manifests itself. In this research, several Computational Intelligence methods have been applied for identifying possible anom... Read More about Anomaly monitoring framework based on intelligent data analysis..

Inferential measurements for situation awareness: enhancing traffic surveillance by machine learning. (2013)
Conference Proceeding
RATTADILOK, P. and PETROVSKI, A. 2013. Inferential measurements for situation awareness: enhancing traffic surveillance by machine learning. In Proceedings of the 2013 IEEE international conference on computational intelligence and virtual environments for measurement systems and applications (CIVEMSA 2013), 15-17 July 2013, Milan, Italy. New York: IEEE [online], article number 6617402, pages 93-98. Available from: https://doi.org/10.1109/CIVEMSA.2013.6617402

The paper proposes a generic approach to building inferential measurement systems. The large amount of data needed to be acquired and processed by such systems necessitates the use of machine learning techniques. In this study, an inferential measure... Read More about Inferential measurements for situation awareness: enhancing traffic surveillance by machine learning..

Statistical optimisation and tuning of GA factors. (2005)
Conference Proceeding
PETROVSKI, A., BROWNLEE, A. and MCCALL, J. 2005. Statistical optimisation and tuning of GA factors. In Proceedings of the 2005 IEEE congress on evolutionary computation (CEC 2005), 2-5 September 2005, Edinburgh, UK. New York: IEEE [online], volume 1, article number 1554759, pages 758-764. Available from: https://doi.org/10.1109/CEC.2005.1554759

This paper presents a practical methodology of improving the efficiency of Genetic Algorithms through tuning the factors significantly affecting GA performance. This methodology is based on the methods of statistical inference and has been successful... Read More about Statistical optimisation and tuning of GA factors..

Multi-objective optimisation of cancer chemotherapy using evolutionary algorithms. (2001)
Conference Proceeding
PETROVSKI, A. and MCCALL, J. 2001. Multi-objective optimisation of cancer chemotherapy using evolutionary algorithms. In Zitzler, E., Thiele, L., Deb, K., Coello Coello, C.A. and Corne, D. (eds.) Proceedings of the 1st International conference on evolutionary multi-criterion optimization (EMO 2001), 7-9 March 2001, Zurich, Switzerland. Lecture notes in computer science, 1993. Berlin: Springer [online], pages 531-545. Available from: https://doi.org/10.1007/3-540-44719-9_37

The main objectives of cancer treatment in general, and of cancer chemotherapy in particular, are to eradicate the tumour and to prolong the patient survival time. Traditionally, treatments are optimised with only one objective in mind. As a result o... Read More about Multi-objective optimisation of cancer chemotherapy using evolutionary algorithms..